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The Beckhard and Harris change formula is a model for whether change will happen – or not.  The formula contains the elements that both drive and resist change in an organization and represent a more complex version of the recovery truism: “The pain of staying the same must be greater than the pain of changing.”  Despite this, the formula does leave some opportunities for improvement, particularly in the arrangement of the math.

The Pain of Staying the Same

To effect change, there must be some “pain” associated with the current situation and way of doing things.  The “pain” can be direct or indirect in the case of missing an opportunity.  Often called FOMO – “fear of missing out” – the awareness that you’re missing out on something can be a powerful motivator for change.

Often in change, the challenge is increasing the awareness of the pain in a way that doesn’t get rejected.  Much like how the “scared straight” programs for anti-drug abuse didn’t work, we can’t often directly tell people how they’re in a pain that they can’t see.  (See Chasing the Scream and The Globalization of Addiction for more on anti-drug abuse programs that used fear and why they didn’t work.)  The work of Carl Rogers and techniques like Motivational Interviewing can be effective for individual change but are not always generalizable to organizational change.  (See A Way of Being for more on Carl Rogers’ contributions.)

Despite the challenges, it’s critical to articulate the pains of the current situation so that the balance scale can be tipped towards a change.

The Pain of Change

Change always comes with some level of discomfort – whether that discomfort is in the additional work to make the change, the uncertainty of the change itself, or in the increased workload that the change may bring.  Change is inherently seen as painful in some sense.  William Bridges’ Transitions Model focuses on the feelings of loss and uncertainty and how they can be seen as resistance or friction in the process.

To be effective, change managers must expose how the proposed change is possible, doable, and better.  The pain of changing needs to be appropriately cataloged to get as accurate a view of the change effort as possible.  It’s too easy for everyone to make the change bigger than it actually is.

The Math

The math of the equation goes like this:

C = [ABD] > X


  • C = Change
  • A = Level of dissatisfaction with the status quo
  • B = Desirability of the proposed or end state
  • D = Practicality of the change
  • X = Cost of changing

The implication is that the degree of change is based on the positive contributions created by dissatisfaction with the status quo, the desirability of the end state, and the practicality of the change.  It’s held back by the perceived cost of changing.  So, to increase the output, you increase dissatisfaction, desirability, or practicality.

The primary problem that I have with the equation is that even though the formula has you multiplying dissatisfaction, desirability, and practicality, the relationship doesn’t appear to be this simple.  If this were the case, then if someone hated the status quo but had no desire for the end state, they’d get a zero for their change – because anything multiplied by zero is that number.

In reality, there is an amplification factor that happens between the forces of constraint (pain of change, perceived (lack of) practicality of the solution) and the forces to drive the change forward like dissatisfaction with the status quo and desirability of the end state.  However, it’s not clear that this can be modeled with a simple multiplication – at least without carefully controlling the scaling of the variables.


As discussed above, the amplification of factors is likely imprecise.  Scaling the factors becomes difficult.  However, this is a good way to evaluate what the forces are that may be acting towards or away from the desired change.  This towards or away from the desired change is akin to Kurt Lewin’s force fields.  (See A Dynamic Theory of Personality for more about Kurt Lewin’s work on force fields.)